ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from AVHRR (1979 - 2023), version 4.0 2017-01
type: Dataset
keyword: DIF10
keyword: ESA
keyword: CCI
keyword: Snow
keyword: Snow Cover Fraction
keyword: orthoimagery
keyword: EARTH SCIENCE>CLIMATE INDICATORS>CRYOSPHERIC INDICATORS>SNOW COVER
keyword: EARTH SCIENCE>SPECTRAL/ENGINEERING>INFRARED WAVELENGTHS
keyword: METOP-A
keyword: METOP-B
keyword: METOP-C
keyword: NOAA-10
keyword: NOAA-11
keyword: NOAA-12
keyword: NOAA-14
keyword: NOAA-16
keyword: NOAA-17
keyword: NOAA-18
keyword: NOAA-6
keyword: NOAA-7
keyword: NOAA-8
keyword: NOAA-9
keyword: TIROS-N
keyword: AVHRR
keyword: AVHRR-2
keyword: AVHRR-3
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keyword: Level 3C
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description: This dataset contains Daily Snow Cover Fraction (snow on ground) from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. Snow cover fraction on ground (SCFG) indicates the area of snow observed from space over land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. The global SCFG product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.The SCFG time series provides daily products for the period 1979-2023. The product V4.0 is based on EUMETSAT Fundamental Data Record (FDR) medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the CLARA-A3 cloud product. The retrieval method of the snow_cci SCFG product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by MetsÃ¤mÃ¤ki et al. (2015) and complemented with a pre-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.63 Âµm and 1.61 Âµm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 Âµm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied using dynamic reference reflectance values (snow, forest, ground) temporally and spatially adapted to consider angle dependencies (sun, view). Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. The following auxiliary data sets are used for product generation: i) ESA CCI Land Cover from 2000; water bodies and permanent snow and i…
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